Clark, AD (2018) Mortality bene ts and intussusception...

Clark, AD (2018) Mortality benefits and intussusception risks of ro-tavirus vaccination in low- and middle-income countries. PhD (re-search paper style) thesis, London School of Hygiene & TropicalMedicine. DOI: https://doi.org/10.17037/PUBS.04651167

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Mortality benefits and intussusception risks of rotavirus vaccination in low- and middle-income countries

ANDREW DAVID CLARK

Thesis submitted in accordance with the requirements for the degree of

Doctor of Philosophy of the University of London

December 2018

Department of Health Services Research and Policy

Faculty of Public Health and Policy

LONDON SCHOOL OF HYGIENE & TROPICAL MEDICINE

Funded in part by research grants from the World Health Organization and Bill and Melinda Gates Foundation

Supervisor: Professor Colin Sanderson

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Signed Declaration

I Andrew David Clark, confirm that the work presented in this thesis is my own. Where

information has been derived from other sources, I confirm that this has been indicated in the

thesis.

Andrew David Clark

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Abstract

Infant rotavirus vaccines have led to substantial reductions in rotavirus gastroenteritis (RVGE)

hospital admissions and costs, but some studies have reported an elevated risk of

intussusception, a rare bowel disorder, in vaccinated infants. The aim of this thesis is to

quantify the potential mortality benefits and intussusception risks of alternative rotavirus

vaccination schedules in 135 low- and middle-income countries (LMICs).

The thesis begins with an introduction to the topic and background to the literature and

concludes with some final reflections on the research and its relevance for informing national

decisions about vaccine safety and optimal scheduling of rotavirus vaccines. The main body

of the thesis includes a series of research papers which address specific topics relevant to the

estimation of mortality benefits and intussusception risks. These include methods for

estimating: RVGE deaths

4

Acknowledgements

I would like to thank Colin Sanderson for his encouragement and expert guidance over the

years. I also thank Mark Jit and Ulla Griffiths for providing helpful suggestions on earlier

drafts. I thank Emma, Ollie and Tom for their support and for inspiring me to get this work

finished.

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Table of contents

Table of abbreviations...6

Chapter 1: Introduction.....8

Chapter 2: Review of the literature.............12

Chapter 3: Aim and objectives of thesis......31

Chapter 4: Estimation of rotavirus deaths in children aged

6

Table of abbreviations

AEFI Adverse Events Following Immunization AD Anderson-Darling statistic AIC Akaikes Information Criterion AIIMS All India Institute of Medical Science ATP According-To-Protocol BCG Bacillus Calmette-Gurin vaccine BCL Brighton Collaboration Level BIC Bayesian Information Criterion BMGF Bill and Melinda Gates Foundation BRV-PV Bovine Rotavirus Pentavalent Vaccine CDC Centers for Disease Control and Prevention CEA Cost-Effectiveness Analysis CFR Case Fatality Ratio CHERG Child Health Epidemiology Reference Group of UNICEF and the WHO CV Cramer-von Mises statistic DHS Demographic and Health Surveys DIC Deviance Information Criterion DTP1 Diphtheria-Tetanus-Pertussis vaccine dose 1 DTP2 Diphtheria-Tetanus-Pertussis vaccine dose 2 DTP3 Diphtheria-Tetanus-Pertussis vaccine dose 3 EIA Enzyme Immunoassay FEC Finnish Extension Trial FUP Follow-up FVI Fully Vaccinated Infants GAVCS Global Advisory Committee on Vaccine Safety GAVI Global Alliance for Vaccines and Immunization GBD Global Burden of Disease Project GE Gastroenteritis GEMS Global Enteric Multicenter Study

GMC Geometric Mean Concentration GNI Gross National Income GRSN WHO-coordinated Global Sentinel Site Rotavirus Surveillance Network

HIC High-Income Country ICD International Classification of Diseases IGME UN Inter-agency Group for Child Mortality Estimation

IHME Institute of Health Metrics and Evaluation IV Intravenous rehydration iVE Instantaneous Vaccine Efficacy IVIR-AC Immunization and Vaccines-related Implementation Research Advisory Committee KDE Kernel Density Estimation KS Kolmogorov-Smirnov statistic LLR Lanzhou Lamb Rotavirus vaccine LMIC Low- and Middle-Income Country LSHTM London School of Hygiene and Tropical Medicine MAE Mean Absolute Error

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MAL-ED Malnutrition and Enteric Disease Study MCEE Maternal Child Epidemiology Estimation Group MCMC Markov Chain Monte Carlo MCRI Murdoch Childrens Research Institute MCV1 Measles-Containing Vaccine dose 1 Meas1 Measles-Containing Vaccine dose 1 MICS Multiple Indicator Cluster Surveys MLE Maximum Likelihood Estimation MMR Measles Mumps and Rubella vaccine MSD Moderate-to-Severe Diarrhoea NIH National Institutes of Health NLS Non-Linear Least Squares NRSN Indian National Hospital Rotavirus Surveillance Network OPV Oral Polio Vaccine ORS Oral Rehydration Salts/Solution PCR Polymerase Chain Reaction PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analyses RCH Royal Childrens Hospital, Melbourne RCT Randomised Controlled Trial REST Rotavirus Efficacy and Safety Trial RMSE Root Mean Squared Error RR Relative Risk RV3-BB Rotavirus Vaccine based on G3 P6 strain (Bishop and Barnes) RVGE Rotavirus Gastroenteritis SAE Severe Adverse Events SAGE Strategic Advisory Group of Experts SCCS Self-Controlled Case Series U5 Under-five years of age UNICEF United Nations International Children's (Emergency) Fund UNPOP United Nations Population Division USAID United States of America International Development VAPP Vaccine Associated Paralytic Poliomyelitis VIMC Vaccine Impact Modelling Consortium WAIFW Who Acquires Infection From Whom WHO World Health Organization WUENIC WHO and UNICEF Estimates of National Immunization Coverage

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1.0 Chapter 1 Introduction

1.1 Benefits and risks of live oral rotavirus vaccines

Rotavirus is an important cause of gastroenteritis (GE) in children aged

9

two doses of Rotarix with DTP1 and DTP2, or three doses of RotaTeq with DTP1,

DTP2, and DTP3 as per current WHO recommendations. The actual age of

administration varies between countries due to differences in national schedules

(target ages for DTP) and differences in the timeliness of vaccination (9). The standard

infant schedules recommended by WHO have demonstrated high and durable efficacy

in low mortality countries but modest efficacy in higher mortality settings (10). This

has stimulated interest in the potential value of a booster dose given with the first dose

of measles-containing vaccine (MCV1, referred to hereafter as Meas1)(11) or a birth

dose given at the same time as Bacillus Calmette-Gurin (BCG)(12). A birth dose has

the potential to prevent disease that occurs very early in life, while a booster dose has

the potential to mitigate the effects of waning rotavirus vaccine protection, a

phenomenon observed in several high mortality settings (10). Birth doses also have

the potential to reduce the number of excess (vaccine-related) intussusception cases

by administering the first dose earlier in life, when the background risk of

intussusception is lower. The optimal number and timing of doses (concurrent with

different combinations of BCG, DTP1, DTP2, DTP3 and Meas1) will depend on

several criteria, including the balance of benefits to risks i.e. number of RVGE deaths

averted per excess intussusception death.

1.3 Scope of the thesis

The aim of this thesis is to quantify the potential mortality benefits (averted RVGE

deaths

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years (Chapter 5); vaccine coverage and timeliness (Chapter 6); rotavirus vaccine

efficacy and waning (Chapter 7); and, intussusception incidence, age distributions and

case fatality ratios - CFRs (Chapter 8). The final research paper (Chapter 9) brings

together this evidence and uses a national vaccine decision support model to estimate

the potential rotavirus mortality benefits and intussusception risks of 18 possible

rotavirus vaccination schedules in 135 LMICs. The thesis concludes with some final

reflections on the research and its relevance for informing national decisions about

vaccine safety and optimal scheduling of rotavirus vaccines (Chapter 10).

This is a research-paper thesis rather than the conventional book style. Six of the

chapters are full research papers. Two have been published in peer-reviewed journals

(Chapters 4 & 6) and the remaining four (Chapters 5, 7, 8 and 9) have been prepared

for submission. For consistency between published and unpublished research papers,

references are listed at the end of each chapter, and the numbering of tables and figures

is restarted at the beginning of each chapter. Each research-paper chapter begins with

a short section describing how the paper contributes to the overall aim and objectives

of the thesis. I have also described my independent academic contribution to each

paper. This is important to clarify because all papers include contributions from

others. Relevant funding and ethical approvals are also described.

Appendices to Chapters 5, 8 and 9 are included at the end of each chapter for ease of

referencing. Other appendices are included at the end of the thesis, either because they

contain optional background material (Appendices 1-5, 10), or because they describe

analyses that were primarily done by others (Appendices 6-9).

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List of references (Chapter 1)

1. Clark A, Black R, Tate J, Roose A, Kotloff K, Lam D, et al. Estimating global, regional and national rotavirus deaths in children aged

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2.0 Chapter 2 Review of the literature

2.1 Rotavirus gastroenteritis

Gastroenteritis (GE), characterised by diarrhoea, abdominal cramps, nausea and

sometimes vomiting, is usually diagnosed when a child experiences three or more

loose stools, or vomiting, within a 24-hour period (1). Without adequate fluid

replenishment GE can quickly lead to dehydration, electrolyte imbalance, metabolic

acidosis, shock and death (2). Descriptions of GE exist as far back as the earliest

records of human civilisation (3) and its role in child mortality is well documented -

described in 1940s London as one of the most fatal diseases of infancy in our

capital(4).

In 1973 Ruth Bishop, Geoffrey Davidson, Ian Holmes and Brian Ruck identified a

high volume of particles of a new virus in the faeces of children admitted to the Royal

Childrens Hospital (RCH) in Melbourne, Australia. The wheel-like structure seen

under an electron microscope was the inspiration for the name rotavirus (rota is latin

for wheel) (5). Prior to this discovery, the causative agents of GE were poorly

understood. Rotavirus has since been detected in numerous studies around the world

and is now recognised as a leading global cause of GE hospitalisations in children

aged

13

Following a brief period of protection from maternal antibodies, almost every child in

the world, irrespective of where they live, will be infected with rotavirus at least once

before their fifth birthday. The mode of transmission is thought to be faecal-oral, and

the incubation period (interval between exposure and onset of symptoms) is usually

less than 48 hours (2). Natural or wild type rotavirus infections (asymptomatic or

symptomatic) have been shown to provide some protection against subsequent

moderate-to-severe disease. Important birth cohort studies have been conducted in

Mexico and India. In Mexico, two prior infections provided complete protection

against subsequent moderate-to-severe disease (10). In India however, two infections

provided only 57% protection (and only 79% after three) (11). In both settings, natural

infections provided limited protection against subsequent asymptomatic infections

and mild disease. Thus frequent reinfections are probably very common and provide

the basis for continued circulation. A study in England detected rotavirus in the stools

of healthy individuals in all age groups (12).

Two point scoring systems have been used to determine the severity of RVGE in

randomised controlled trials (RCTs), the 20-point Vesikari system and the 24-point

Clark system (13). Points are awarded for the presence and severity of different

symptoms e.g. duration of vomiting, duration of diarrhoea, rectal temperature, signs

of dehydration etc. Nearly all RCTs of rotavirus vaccines define severe RVGE as 11-

20 points on the Vesikari scale. Some older trials use a Clark score of 16-24 points.

These two scores have been shown to correlate poorly with one another when

estimating the proportion of RVGE episodes defined as severe (13, 14).

In the scientific literature, the most commonly reported rotavirus disease burden

indicator is the rotavirus-positive proportion among GE hospital admissions aged

14

vomiting and diarrhoea, intravenous rehydration (IV) is required in more serious cases

(16).

Estimates of the number of RVGE deaths

15

A good deal of pre- and post-licensure evidence has now been accumulated on the

efficacy and safety of Rotarix and RotaTeq. Both vaccines have demonstrated

>90% efficacy against severe RVGE episodes in low mortality settings. However, the

combined estimate of efficacy from higher mortality countries (Bangladesh, Vietnam,

Ghana, Kenya and Mali) is only around 67% in the first year of life and 34% in the

second year of life (24). The reason for lower and less durable efficacy in these

settings is unclear but has been linked to factors including poorer nutritional status

and more frequent exposure to a wider range of enteric pathogens (25). Both vaccines

have demonstrated clinical cross-protection to the major strains not included in the

vaccines (26), and thus similar efficacy in different settings. It is difficult to compare

the two vaccines directly as different case definitions and severity scales were used in

some trials (13) and the two vaccines have never been directly compared in a head-

to-head RCT within the same study population. However, the post-licensure

experience of countries that have used both Rotarix and RotaTeq does not suggest

any material difference in impact (27).

In recent years, several manufacturers have emerged from LMICs. In China, LLR

(Lanzhou lamb rotavirus vaccine - Lanzhou Institute of Biological Products) is based

on a single G10P[12] lamb rotavirus strain, and has been sold in the private market

since 2000. A case control study of LLR in China reported effectiveness of 43% for

a single dose administered between 2 and 35 months of age (28). In Vietnam,

Rotavin (POLYVAC-Vietnam) is based on an attenuated human G1P[8] strain

isolated from a Vietnamese child. This vaccine was licensed for use after

demonstrating comparable immunogenicity to Rotarix among Vietnamese infants

(29). In India, two vaccines have been developed. ROTAVAC (Bharat Biotech

International, India) was recently WHO pre-qualified for global use (30). This is based

on a naturally attenuated human-bovine (cow) strain (II6E) isolated from an Indian

infant by Maharaj K Bahn and colleagues at the All India Institute of Medical Sciences

(AIIMS) in Delhi (31). This vaccine demonstrated 54% efficacy against severe RVGE

in Indian infants and is priced at less than $3 per three-dose course. This is

considerably lower than the price of Rotarix and RotaTeq. A bovine-human

reassortant pentavalent rotavirus vaccine (BRV-PV) called ROTASIIL (Serum

Institute of India) is also licensed for use in India. This has demonstrated 38% efficacy

against severe RVGE in India, and 65% efficacy in Niger (32, 33). This vaccine may

also be WHO pre-qualified for global use soon.

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Several others rotavirus vaccines are also in the pipeline, including neonatal and non-

replicating injectable vaccines (34, 35). An oral neonatal vaccine, RV3-BB (Murdoch

Childrens Research Institute - MCRI, Australia) has shown to be efficacious in

Indonesia when administered as a three-dose series (36). This has the potential to

increase vaccination coverage and potentially reduce vaccine-related intussusception

events by allowing the first dose to be administered earlier in life when the

background rate of intussusception is low. Other vaccines in the pipeline include non-

replicating injectable vaccines (35). These could prove to be safer and more

efficacious than existing live oral vaccines, but more clinical evidence will be needed

to confirm this.

2.3 Rotavirus vaccination and intussusception

Intussusception is the main cause of bowel obstruction in children aged

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associated with an increased risk of intussusception in some settings (38, 39). While

the scale of risk associated with Rotarix and RotaTeq is believed to be smaller

than the risk observed for RotaShield, a true comparison is not possible because

both vaccines have been administered within age windows designed to avoid the

background peak age of intussusception. Many of the vaccines administered in the

RotaShield programme were administered as part of a catch-up campaign, so were

administered to older infants when the background incidence of intussusception was

high (40). To limit the scale of potential vaccine-related intussusception cases the two

major vaccine manufacturers have recommended different age restrictions tailored to

their own vaccines. The aim of these age restrictions is to ensure the vaccine is

administered earlier in life, when the background incidence of intussusception is

lower. The WHO harmonised the different manufacturers age restrictions and

recommended administration of the first dose before 15 weeks of age and the final

dose before 32 weeks of age (24). Following a modelling analysis in 2012, the WHO

revised their recommendation to allow countries to remove age restrictions in

countries where the benefits of later vaccination would greatly exceed the risks (24,

41).

An excess or vaccine-related case of intussusception is defined by WHO as an adverse

event following immunization (AEFI). Intussusception is a serious adverse event

because it has the potential to lead to hospitalisation and death. Serious adverse events

are included within the wider spectrum of all severe adverse events (SAE). SAEs also

include severe reactions that are not life-threatening. The distinction between

serious and severe is important; serious is a regulatory term whereas severe is not

(42).

Different study designs have been used to detect any potential relative risk of

intussusception following vaccination, but because intussusception is such a rare

event, these studies are often not powered for reliable detection of an increase in risk.

The self-controlled case series (SCCS) methodology is considered to be relatively

reliable and has been widely used (5). In this method, children with intussusception

act as their own controls. The risk of intussusception is calculated for the period of

hypothesised elevated risk (i.e. 21 days following vaccination) and then compared to

the risk of intussusception in all other periods, with appropriate adjustment for age

(43). Intussusception risk is expressed as the relative incidence (RI) or relative risk

(RR) compared to the expected background incidence in the absence of vaccination.

A meta-analysis of Rotarix studies by Stowe et al found pooled RI estimates of 2.4

18

(95% confidence interval 1.5 - 3.8) and 1.8 (1.3 - 2.4) in the 21 day period after the

first and second doses, respectively (44). Similar risks have also been reported for

RotaTeq in the USA (39) and Australia (38). The estimates for Rotarix and

RotaTeq in Australia were equivalent to one additional case in every 14,000-20,000

vaccinated infants, but studies from other settings have reported a lower level of risk,

and none have reported a risk as high as RotaShield (one in every 5,000-10,000

vaccinated infants). Encouragingly, a recent SCCS study of Rotarix in Africa found

no elevated risk of intussusception in the first 1-7 days after dose 1 (RI 0.30, 95% CI

0.0 - 1.0) or dose 2 (RI 0.8, 95% CI 0.2 1.7) and no elevated risk 8-21 days after

dose 1 (RI 1.0, 95% CI 0.3 2.3) or dose 2 (RI 0.7, 95% CI 0.4 1.2). This was a

multi-site study including infants from seven countries (Ethiopia, Ghana, Kenya,

Malawi, Tanzania, Zambia, and Zimbabwe) (45).

2.4 Published studies evaluating the benefits and risks of rotavirus vaccination

In 2012, Patel et al estimated the potential mortality benefits and intussusception risks

of introducing live oral rotavirus vaccines into the 2010 birth cohort of 158 countries

(24). This study updated an earlier analysis conducted in 2009 based on 117 countries

(46). The 2012 study found that with full adherence to the manufacturers age

restrictions, universal introduction of rotavirus vaccination would prevent 156,000

RVGE deaths and cause 253 deaths (benefit-risk ratio of ~600:1). Without age

restrictions, rotavirus vaccines were estimates to prevent 203,000deaths and cause 547

deaths (benefit-risk ratio of ~370:1). The study therefore found that removing age

restrictions from a standard infant schedule co-administered with DTP would prevent

an additional ~47,000 RVGE deaths and potentially cause an additional ~300

intussusception deaths each year (incremental benefit-risk ratio of 154:1)(24). This

study informed a WHO recommendation to remove the manufacturers age

restrictions for vaccination given that the benefits of preventing additional rotavirus

mortality from later vaccination greatly exceeded the intussusception risks (41). The

2012 publication (Appendix 1) and WHO position paper (Appendix 2) are available

in the list of appendices.

Several other benefit-risk analyses have also been published. A multi-country analysis

for all countries in Latin America estimated a benefit-risk ratio of 395:1 (47), while

in a study in Brazil and Mexico the estimate was 260:1 (48). The benefit-risk ratio

was estimated to be 88:1 in England (18), 273:1 in France (49), 77:1 in the USA (50)

and 366:1 in Japan (51). Other high income countries have calculated benefits and

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risks for hospitalisations, but not mortality (38). In higher income countries, mortality

from both rotavirus and intussusception is very rare, and other criteria become more

important. In England, Clark et al estimated that Rotarix would cause one additional

intussusception admission in every 18,551 vaccinated English infants (5th and 95th

percentiles, 6,728 - 93,952), equivalent to 35 additional intussusception admissions

each year. In contrast, it was estimated that each year the vaccine prevented three

rotavirus deaths, 13,000 rotavirus admissions, 27,000 rotavirus emergency visits and

74,000 rotavirus GP consultations in children aged

20

influence on vaccine impact estimates. In contrast, waning duration of protection was

shown to have an important influence in some of the analyses. Only one (2%) of the

models explicitly modelled the natural history of disease and associated herd effects

(54). Postma et al compared estimates from three models and attributed differences in

results to assumptions about dose-specific vaccine efficacy, waning duration of

protection and the level of immunity acquired from natural infections (55). The

timeliness of vaccination was shown to be influential in a cost-effectiveness study by

Clark et al in Peru. This analysis showed that ignoring delays and assuming on-time

vaccination would over-estimate health benefits by 4% (56). An analysis of delays in

45 other countries by Clark and Sanderson showed that Perus immunization

programme is relatively timely compared to others, so this error is likely to be greater

in countries with more pronounced delays (57).

Unlike static cohort models, transmission dynamic models are able to predict the

number of susceptible, infectious and immune individuals over time. These models

are also able to capture the interplay between immunity acquired from vaccination

and immunity acquired from repeated natural (wild type) infections. Models of this

kind typically require assumptions to be made about the number of individuals

exposed by each infectious individual (also known as the basic reproductive number

or R0), the duration of immunity acquired from natural infections, and further

assumptions about who acquires infection from whom (WAIFW). Pitzer et al

described five rotavirus transmission dynamic models that were each calibrated to the

same age-specific RVGE incidence data from England and Wales (58). All five

models simulated the flow of groups of individuals into different compartments

(health states) over time using differential equations. A pivotal study by Velasquez et

al was used to inform estimates of protection from 1 up to 4 natural infections against

subsequent infections and disease episodes (10). Estimates of R0 varied considerably

between the five models, ranging from ~1 to 26 secondary exposures per infectious

individual. Discrepancies between the model predictions reflected uncertainties in the

age-specific risk of RVGE infections, and the duration of natural and vaccine-induced

immunity. However, over the long-term (5 years post-vaccination), all of the models

predicted impact among children aged

21

better fit to the local data. The authors found a marginal role for herd effects in

explaining overall impact (~1% of the total long-term impact in children aged

22

Graphical depiction of the trolley problem

Source: https://i0.wp.com/moralarc.org/wp-content/uploads/2015/04/trolley-problem.jpg?w=620

Another variation is that a person is pushed from a bridge into the path of the tram,

again saving five lives at the expense of one. The moral dilemma is a choice between

inaction and intervention. Utilitarianism (the greatest good for the greatest number)

would favour intervention (69). In the context of rotavirus vaccination this would

mean favouring schedule options that maximise the net number of deaths prevented,

irrespective of whether large number of intussusception deaths are caused in the

process. This raises important ethical considerations and is contrary to the public

health principle first do no harm (67). It also fails to consider uncertain

consequences that could be associated with taking action. For example, an increase in

high profile legal challenges and anti-vaccine sentiment could have an adverse effect

on the coverage of rotavirus vaccines, and potentially other vaccines. In England,

concerns about the safety of whole-cell pertussis and MMR (measles mumps and

rubella) vaccines have previously led to substantial short-term declines in coverage

(65). There is also some evidence that a death caused by action/intervention may be

perceived by individuals as worse than a death caused by inaction (70, 71).

Herbert Simon made a distinction between substantive rationality, choosing the

outcome with the maximum mathematical utility, and procedural rationality, allowing

decision makers to reject options that do not meet minimum standards (72). In terms

https://i0.wp.com/moralarc.org/wp-content/uploads/2015/04/trolley-problem.jpg?w=620

23

of rotavirus vaccination, this would imply a maximum level of acceptable risk, above

which the vaccination programme would not be socially acceptable. The risk

associated with RotaShield in the USA (more than one excess intussusception cases

in every 10,000 vaccinated infants) provides an important psychological benchmark

for what might be considered a maximum level of acceptable risk. Fine and Clarkson

have argued that the level of acceptable risk will differ depending on whether the

choice is made by individuals (more likely to choose lower uptake) or public health

decision-makers representing the community as a whole (more likely to choose higher

uptake) (73). Another benchmark that could be used to inform a socially acceptable

risk for rotavirus vaccines is the level of risk that has been accepted for other vaccines.

However, combining this evidence is not straightforward. The WHO provides

reported reaction rates for each vaccine formulation but the spectrum of possible

adverse effects is broad and the uncertainty intervals around the risks are wide. For

BCG vaccine, the risk of disseminated BCG disease (fatal in 50% of cases) is reported

to be less than one in every 200,000 vaccinated infants. For the first dose of oral polio

vaccine (OPV) the risk of vaccine associated paralytic poliomyelitis (VAPP) is one in

every 750,000 vaccinated infants. For Measles and DTP vaccines, rates of febrile

seizures are relatively common (one in every ~3000 doses) but these are rarely fatal

(42, 74). Resnik has argued that the maximum level of acceptable risk should not

exceed the maximum risk of death for high risk forms of paid labour, such the

mortality risks among fishermen, loggers and extraction workers. He went on to

suggest this as one possible approach for determining the maximum acceptable risk

among paid volunteers in clinical trials. The maximum acceptable risk of a serious

adverse event could then be derived by combining the maximum acceptable mortality

risk with the CFR for the serious adverse event in question (75). This approach has

obvious limitations if applied to the example of rotavirus vaccination because the

focus is on adults and paid participation.

For rotavirus vaccination, the maximum acceptable risk will be inextricably linked to

the scale of potential benefits and for this reason, it would be very difficult for national

decision-making committees to set universal thresholds for maximum acceptable risk.

A minimum threshold for the balance of benefits to risks (minimum benefit-risk ratio)

could however be developed, and may lead to more consistent decision-making across

vaccines. The Global Advisory Committee on Vaccines Safety (GACVS) and

Strategic Advisory Group of Experts (SAGE) are the principal advisory groups to

WHO on issues around the safety and acceptability of rotavirus vaccines, and

ultimately the committee members will have to make value judgements and

24

recommendations informed by the best available evidence on benefits and risks, as

well as other criteria including costs, cost-effectiveness and operational feasibility

(76).

25

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Association of Rotavirus Vaccine Introduction and Reduction in All-Cause Childhood Diarrheal Hospitalizations in South Africa. Clin Infect Dis. 2016;62 Suppl 2:S188-95.

3. Lim ML, Wallace MR. Infectious diarrhea in history. Infect Dis Clin North Am.

2004;18(2):261-74. 4. Gairdner P. Infantile diarrhoea: An Analysis of 216 Cases with Special Reference to

Institutional Outbreaks. Arch Dis Child. 1945;20(101):22-7. 5. Bishop R. Discovery of rotavirus: Implications for child health. J Gastroenterol

Hepatol. 2009;24 Suppl 3:S81-5. 6. Clark A, Black R, Tate J, Roose A, Kotloff K, Lam D, et al. Estimating global,

regional and national rotavirus deaths in children aged

26

14. Aslan A, Kurugol Z, Cetin H, Karakaslilar S, Koturoglu G. Comparison of Vesikari and Clark scales regarding the definition of severe rotavirus gastroenteritis in children. Infect Dis (Lond). 2015;47(5):332-7.

15. Kotloff KL, Blackwelder WC, Nasrin D, Nataro JP, Farag TH, van Eijk A, et al. The

Global Enteric Multicenter Study (GEMS) of diarrheal disease in infants and young children in developing countries: epidemiologic and clinical methods of the case/control study. Clin Infect Dis. 2012;55 Suppl 4:S232-45.

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31

3.0 Chapter 3 - Aim and objectives of thesis

3.1 Aim

The aim of this thesis is to estimate the potential mortality benefits (averted RVGE

deaths aged

32

4.0 Chapter 4 - Estimation of rotavirus deaths in children aged

33

4.3 Ethical approval

Appendix 3 (Chapter 4, S1 Table, Information about the data used for new analyses)

describes the ethical approvals obtained by all collaborators/co-authors involved in

this work. I did not seek LSHTM ethical approval for my contribution to the paper

because my analysis was based on publicly available datasets and published papers in

the public domain. I had no access to files with patient identifiable data and did not

analyse or have access to any primary databases.

RESEARCH ARTICLE

Estimating global, regional and national

rotavirus deaths in children aged

watery diarrhoea deaths. 97% (95% CI 9598%) of the U5 diarrhoea hospitalisations that

tested positive for rotavirus were entirely attributable to rotavirus. For all clinical syndromes

combined the rotavirus attributable fraction was 34% (95% CI 3136%). This increased by a

factor of 1.08 (95% CI 1.021.14) when the GEMS results were reanalysed using a more

sensitive molecular test.

Conclusions

We developed consensus on seven proposals for improving the quality and transparency of

future rotavirus mortality estimates.

Introduction

Rotavirus is a leading cause of diarrhoeal mortality in children less than five years old (U5),

but there is considerable disagreement about how many rotavirus deaths occur each year.

Recent estimates from different sources range from ~120,000 to ~215,000 [13]. Accurate

rotavirus mortality estimates help governments and donors prioritise public health interven-

tions and provide a basis for assessing the impact of immunization on mortality rates. Conflict-

ing estimates from different sources create confusion and can delay the introduction of

important diarrhoea mortality prevention measures, such as rotavirus vaccines.

In recent years, three groups have produced estimates of rotavirus deaths:

1. CHERGthe Child Health Epidemiology Reference Group of the World Health Organiza-

tion (WHO) and UNICEF. CHERG is now referred to as MCEEthe Maternal and Child

Epidemiology Estimation group;

2. GBDthe Global Burden of Disease Study, a collaboration led by the Institute for Health

Metrics and Evaluation (IHME); and,

3. WHO/CDCthe WHO and Centers for Disease Control and Prevention (joint estimates).

A meeting coordinated by WHO (Geneva, March 2015) facilitated the initial discussions on

the differences between the currently available rotavirus mortality estimates. This work builds

on a previous assessment of differences between CHERG and GBD estimates of all-cause U5

diarrhoea deaths [4]. Several gaps in the evidence were identified at an early stage in the pro-

cess, and one important task was to conduct new analyses to help bridge these gaps. First, rota-

virus is not associated clinically with acute bloody (dysenteric) diarrhoea and rarely with

persistent diarrhoea (of 14 days duration or more). As a result, many of the rotavirus-positive

proportions reported in hospital surveillance networks, and in the literature, exclude these

cases, and simply report the rotavirus-positive proportion among hospitalised children with

acute watery diarrhoea. If this proportion is applied to all episodes of diarrhoea resulting in

hospitalisation, it will result in overestimates. Second, there is very limited evidence to inform

whether the distribution of clinical syndromes for U5 diarrhoea hospitalisations (% acute

watery, % acute bloody, % persistent) is similar to, and thus a reasonable proxy for, the distri-

bution of clinical syndromes for U5 diarrhoea deaths. Most approaches assume that rotavirus-

positivity among diarrhoea hospitalisations is a reasonable proxy for rotavirus-positivity

among diarrhoea deaths. However, the two proportions are rarely reported in the same study

population. Third, to date there has been no explicit quantification of the rotavirus attributable

Estimating rotavirus deaths in children aged

fraction among U5 diarrhoea hospitalisations, or the extent to which that varies depending on

the type of diagnostic test used.

The aim of this manuscript is to compare the existing rotavirus mortality estimates, explain

the reasons for differences, provide evidence to inform key areas of uncertainty, and propose

improvements for future estimates.

Methods

We used a range of methods and sources of data. First, we compared existing estimates of U5

rotavirus deaths at the global, regional and national level and identified key differences in the

approaches used. Second, we used data from a large number of hospitals to estimate the pro-

portion of U5 diarrhoea hospitalisations that were acute watery, acute bloody and persistent.

Third, we used data from verbal autopsy studies to estimate the proportion of U5 diarrhoea

deaths that were acute watery, acute bloody and persistent. Fourth, we calculated the propor-

tion of U5 diarrhoea hospitalisations and U5 diarrhoea deaths that were rotavirus-positive in

each of the African and Asian sites included in the Global Enteric Multicenter Study (GEMS).

Fifth, we used data from GEMS to estimate the proportion of rotavirus-positive U5 diarrhoea

hospitalisations that were entirely attributable to rotavirus, and quantified the increase in the

rotavirus attributable fraction when a more sensitive molecular test was used to determine

rotavirus-positivity.

All data used in this study were anonymized prior to access and analysis. Please see support-

ing information (S1 Table) for details about institutional ethical approvals, and how and where

the data were collected.

U5 rotavirus deaths: Comparison of estimates from GBD, CHERG and

WHO/CDC

An independent reviewer (AC) compared the methods and data files published by the Global

Burden of Disease 2013 Study (GBD 2013) [1, 5], CHERG [2, 6] and WHO/CDC [3, 7]. GBD

provided a data file with country specific estimates of U5 rotavirus deaths [8].

We compared global, regional and national estimates of U5 deaths, U5 diarrhoea deaths

and U5 rotavirus deaths for the year 2013 using a standard list of 186 countries (S1 File).

CHERG did not report country estimates of U5 rotavirus deaths, so we multiplied country

estimates of U5 diarrhoea deaths for the year 2013 by regional estimates of the proportion of

U5 diarrhoea deaths due to rotavirus, as reported by CHERG for the year 2010. We removed

two countries from the GBD list (Taiwan, Palestine) and seven from the WHO/CDC list

(Cook Islands, Monaco, Nauru, Niue, Palau, St Kitts and Nevis, San Marino, Tuvalu) because

they did not appear in both GBD and WHO/CDC datasets. GBD, CHERG and WHO/CDC

used different classifications for grouping countries. For the purpose of this comparison exer-

cise, all countries were grouped using the WHO classification system i.e. AFRO, AMRO,

EMRO, EURO, SEARO, WPRO [9].

Clinical syndromes of U5 diarrhoea hospitalisations: Acute watery, acute

bloody, persistent

To estimate the proportion of U5 diarrhoea hospitalisations that were acute watery, acute

bloody and persistent, we used data from 84 hospitals in 9 countries:

1. 50 hospitals (5 in Indonesia, 42 in Rwanda and 3 in Zambia) from the WHO-coordinated

Global Sentinel Site Rotavirus Surveillance NetworkGRSN [10];


2. 7 hospitals from the Indian National Hospital Rotavirus Surveillance NetworkNRSN

(Delhi, Hyderabad, Kolenchery, Ludhiana, Tirupati, Trichy and Vellore); and;

3. 27 hospitals included in the Global Enteric Multicenter StudyGEMS (1 in Bangladesh, 4

in India, 6 in Gambia, 10 in Kenya, 6 in Mozambique). Methods for recruiting and enroll-

ing moderate-to-severe diarrhoea (MSD) cases in GEMS have been described in detail else-

where [11]. We included 5 of the 7 GEMS sites in this particular analysis. Mali and Pakistan

were excluded because they rarely hospitalised children [12].

To be included, sites had to be major paediatric hospitals or district hospitals with100

children aged

more than 9 children with MSD were identified in a fortnight, only the first 9 children were

enrolled and tested for rotavirus; the remainder were recorded on a log and assumed to have

the same rotavirus-positive proportion as enrolled cases that were identified in the same fort-

night, age stratum (0-11m, 12-23m, 24-59m) and diarrhoea syndrome (acute watery, acute

bloody, persistent).

We also calculated the proportion of U5 deaths that: a) tested positive for rotavirus within 7

days of death; and, b) had diarrhoea coded as the first or second cause of death on their verbal

autopsy (VA) report. Rotavirus-positive children with a missing VA report (~20%) were

assumed to have the same cause-of-death breakdown as rotavirus-positive children with a VA

report.

For completeness, we also calculated the rotavirus-positive proportion among healthy con-

trols as well as MSD cases that were not admitted to hospital.

Proportion of rotavirus-positive U5 diarrhoea hospitalisations attributable

to rotavirus in GEMS

GEMS tested for a wide range of enteric pathogens in the stools of MSD cases and healthy

community controls without diarrhoea matched to cases by age, gender, and residence; con-

trols were enrolled within 14 days of the index case. GEMS also included information about

whether MSD cases were admitted to hospital or not.

We used multiple conditional logistic regression to calculate the odds ratio of rotavirus EIA

positivity in hospitalized MSD cases vs matched healthy controls adjusted for the presence of

other pathogens. All syndromes of diarrhoea were included. We then calculated the attribut-

able fraction (AF) as described by Bruzzi et al [15]. These methods were the same as those usedto estimate attributable fractions in the main GEMS analysis [12, 16]. However, we restricted

the analysis to hospitalised cases, thought to be a better proxy for estimating rotavirus-

attributable mortality than all MSD cases. We excluded Mozambique from all AF analyses due

to concerns about the quality of the EIA testing, and did not estimate individual AFs for Mali

and Pakistan because hospitalisation for diarrhoea was very rare in these sites.

Using these attributable fractions, which represent the fraction of hospitalised MSD cases

with disease attributable to rotavirus, we calculated the attributable fraction among the

exposed (AFe). The AFe represents the fraction of rotavirus positive cases who have disease

caused by rotavirus. The rotavirus-positive proportions used to derive the AF and AFe were

based only on the children with MSD that were tested for rotavirus. These were age-specific

(0-11m, 12-23m, 24-59m) and did not involve extrapolation to non-enrolled MSD cases.

Finally, we used previously described methods [17] to calculate the rotavirus attributable

fraction based on quantitative Polymerase Chain Reaction (qPCR). We restricted the analysis

to a subset of 721 hospital cases and matched controls, and calculated the AF for all country

sites combined, excluding Mozambique. To quantify the test performance of EIA compared to

qPCR, we repeated this analysis for EIA test results, and calculated the ratio between the two

attributable fractions. All syndromes of diarrhoea were included. Confidence intervals were

calculated by bootstrapping with 1000 iterations.

Results

Comparison exercise

GBD produce their own estimates of U5 deaths [18], whereas CHERG and WHO/CDC use

U5 deaths from the UN Inter-agency Group for Child Mortality Estimation (IGME)[19]. Both

GBD and IGME estimate approximately 6.3 million U5 deaths globally in 2013 (Table 1) but


some important differences exist at country/regional levels e.g. ~739,000 (GBD) vs ~845,000

(IGME) in the Eastern Mediterranean Region (EMRO). The main methodological differences

between GBD and IGME have been described in detail elsewhere and include the choice of

data points selected (vital registration, census and household surveys) and fitting methods

used [20].

GBD and CHERG produce their own estimates of the proportion of U5 deaths due to diar-

rhoea [5, 6]; WHO/CDC use the CHERG estimates. GBD and CHERG estimated that 89% of

U5 deaths were caused by diarrhoea at the global level in the year 2013 (Table 1). Differences

in GBD and CHERG estimates for the South East Asia (SEARO) region (6% vs 10%) are driven

by differences in estimates for India (6% vs 10%) where U5 diarrhoea deaths are ~80,000 vs

~140,000 respectively (Table 1). In other regions there is more agreement. Estimates for the

African (AFRO) region are consistent overall (10% vs 10%) but there are still large differences

at country level e.g. Zimbabwe (Fig 1).

Methodological differences between GBD and CHERG have been described in detail else-

where [4]. In brief, CHERG excluded verbal autopsy studies that only investigated a single

cause of death and data points from incomplete vital registration systems in higher mortality

Table 1. Comparison of CHERG, GBD and WHO/CDC estimates of U5 deaths, U5 diarrhoea deaths and U5 rotavirus deaths in the year 2013 by

WHO region, and for selected large countries.

GLOBAL AFRO AMRO EMRO EURO SEARO WPRO Bangladesh DR

Congo

India Indonesia

U5 deaths

UN (IGME) used by

CHERG

6,282,254 2,977,576 227,475 845,286 136,850 1,700,178 394,889 129,433 319,977 1,340,055 136,371

GBD 6,271,643 3,164,861 248,643 738,702 130,573 1,604,028 384,836 128,228 340,416 1,249,673 148,807

WHO/CDC - - - - - - - - - - -

Proportion of U5 deaths

due to diarrhoea

CHERG 0.09 0.10 0.04 0.10 0.04 0.10 0.06 0.06 0.11 0.10 0.06

GBD 0.08 0.10 0.05 0.12 0.03 0.06 0.02 0.01 0.17 0.06 0.06

WHO/CDC - - - - - - - - - - -

U5 diarrhoea deaths

CHERG 577,508 293,289 9,297 84,592 5,689 162,298 22,344 8,298 33,730 140,451 7,505

GBD 519,485 312,297 11,923 88,071 3,694 94,574 8,926 1,715 57,344 80,188 8,694

WHO/CDC 577,508 293,289 9,297 84,592 5,689 162,298 22,344 8,298 33,730 140,451 7,505

Proportion of U5

diarrhoea deaths due to

Rotavirus

CHERG 0.27 0.27 0.23 0.31 0.26 0.26 0.33 0.26 0.27 0.26 0.26

GBD 0.24 0.24 0.18 0.18 0.26 0.27 0.42 0.12 0.13 0.26 0.37

WHO/CDC 0.37 0.39 0.26 0.36 0.31 0.35 0.43 0.33 0.40 0.34 0.50

U5 rotavirus diarrhoea

deaths

CHERG 157,398 78,601 2,176 26,477 1,473 41,386 7,284 2,116 9,040 35,815 1,914

GBD 122,322 73,758 2,178 15,984 976 25,637 3,790 202 7,523 21,205 3,176

WHO/CDC 215,757 115,023 2,455 30,577 1,752 56,287 9,664 2,723 13,526 47,082 3,771

Region and global estimates may differ from official WHO/CDC, CHERG and GBD estimates because a standard set of countries and regions was used and

no rounding was done prior to aggregation.

https://doi.org/10.1371/journal.pone.0183392.t001


settings. GBD included these data points and adjusted for missing data. GBD also included

unpublished data points obtained under third party data use agreements whereas CHERG

only use publicly available data points [21].

All three groups produce their own estimates of the proportion of U5 diarrhoea deaths that

are attributable to rotavirus. For the year 2013, the global proportions were 24% (GBD), 27%

(CHERG) and 37% (WHO/CDC). These correspond to 122,322 (GBD), 157,398 (CHERG)

and 215,757 (WHO/CDC) U5 rotavirus deaths (Table 1). Fig 2 shows the extent of variation in

the fraction of diarrhoea deaths attributed to rotavirus across countries within each WHO

region. There are large differences in some countries; for example, in DR Congo the propor-

tions are 13% (GBD), 27% (CHERG) and 40% (WHO/CDC).

The three groups used different methods to:

1. select data points (rotavirus-positive proportions);

2. extrapolate data points to individual countries;

3. account for rotavirus vaccine coverage;

4. convert rotavirus-positive proportions to rotavirus attributable fractions; and,

5. calculate uncertainty ranges.

A more detailed description of these differences can be found in the supporting informa-

tion (S1 Appendix).

Fig 1. Country-level differences in GBD vs CHERG estimates of the proportion of U5 deaths due to

diarrhoea in the year 2013 by WHO region.

https://doi.org/10.1371/journal.pone.0183392.g001


Clinical syndromes for U5 diarrhoea hospitalisation

Table 2 shows the distribution of clinical syndromes for U5 diarrhoea hospitalisations for vari-

ous sites in Africa and Asia. A meta-analysis including data from all GRSN, NRSN and GEMS

sites suggests that acute watery diarrhoea was associated with 87% (95% CI 8390%) of U5

diarrhoea hospitalisations (Fig 3) but there was substantial evidence for heterogeneity (I-

squared 99.08%, p = 0.00) between the studies. The GEMS site in Bangladesh (Mirzapur) had a

very high rate of acute bloody diarrhoea for reasons that are not clear.

Clinical syndromes for U5 diarrhoea deaths

Table 2 shows the distribution of clinical syndromes for U5 diarrhoea deaths. A meta-analysis

suggests that acute watery diarrhoea was associated with 65% (95% CI 5774%) of U5 diar-

rhoea deaths (Fig 4) but again there was substantial evidence for heterogeneity between the

studies (I-squared 92.06%, p = 0.00). In four of the nine countries with verbal autopsy data, the

clinical syndromes of diarrhoea deaths were compared for those who died in any type of health

facility and those who died in the home, as reported by the family respondent. Most of deaths

were in the home (Cameroon 70%, Malawi 50%, Niger 86% and Nigeria 78%) but the distribu-

tion of acute watery, acute bloody and persistent diarrhoea was similar irrespective of the place

of death (Kalter, personal communication).

Rotavirus-positive proportion in U5 diarrhoea hospitalisations and U5

diarrhoea deaths in GEMS

For all GEMS sites combined (excluding Mozambique), rotavirus was detected (EIA-positive)

in 44% of acute watery U5 diarrhoea hospitalisations (55% in Asia, and 32% in Africa)

Fig 2. Country-level variation in the fraction of U5 diarrhoea deaths due to rotavirus in the year 2013

by source of estimates and by WHO region.



Table 2. Number and proportion of acute watery, acute bloody and persistent cases among U5 diarrhoea hospitalisations and U5 diarrhoea deaths

in various settings before rotavirus vaccine introduction.

Source Study

location

Study type Study

period

Diarrhoea

outcome

Age Total

n

Acute

Watery

n

Acute

Bloody

n

Persis-tent*n

Acute

Watery

%

Acute

Bloody

%

Persis-tent

%

Clinical syndromes of U5 diarrhoea hospitalisations

GRSN Indonesia Surveillance

hospitals (n = 5)

201415 Inpatients

Fig 3. Meta-analysis showing the proportion of U5 diarrhoea hospitalisations associated with acute

watery diarrhoea (AWD) for selected sites in Africa and Asia.


Fig 4. Meta-analysis showing the proportion of U5 diarrhoea deaths associated with acute watery

diarrhoea (AWD) for selected sites in Africa and Asia.



(Table 3). When all clinical syndromes of diarrhoea were included, the rotavirus-positive pro-

portion was 38% (44% in Asia; 30% in Africa).

Rotavirus was detected (EIA-positive) in 32% (12/37) of children aged

Proportion of rotavirus-positive U5 diarrhoea hospitalisations attributable

to rotavirus in GEMS

The AFe value (equivalent to the rotavirus attributable fraction among rotavirus-positive U5

diarrhoea hospitalisations) was 0.97 (95% CI 0.950.98) for all included GEMS sites (Table 4)

and all diarrhoea syndromes combined.

Using qPCR instead of EIA for rotavirus detection increased the AF by a factor of 1.08

(95% CI 1.021.14).

Proposed improvements

We propose a number of improvements for consideration by all groups involved in the devel-

opment of future rotavirus mortality estimates.

Reporting a standard set of minimum variables to describe all input data

points

Previous comparison exercises have stressed the need for input data points to be made avail-

able at the time estimates are published [4, 20]. Recent Guidelines for Accurate and Transpar-

ent Health Estimates Reporting (GATHER) have recommended publication of a spreadsheet

table with details about the data points used to inform estimates [22]. These guidelines do not

provide explicit guidance on the variables that should be reported. We suggest that the follow-

ing standard set of minimum variables should be reported: (a) author/reference; (b) country;

(c) sub-national location; (d) data collection period; (e) age range; (f) type of study; (g) type of

diagnostic test; (h) number of enteric pathogens tested; (i) inpatient/outpatient; (j) pre/post

Table 4. Rotavirus positive proportion, attributable fraction (AF) and attributable fraction in the exposed (AFe) for MSD cases

implementation of rotavirus vaccine in the public sector, or preferably a more precise estimate

of rotavirus vaccine coverage with details about the source of sub-national or national coverage

data used; (k) type of clinical syndrome e.g. acute watery, all syndromes; (l) included/excluded

in final estimates; (m) justification if excluded; (n) rotavirus-positive proportion (unadjusted);

(o) rotavirus-positive proportion (adjusted); and, (p) description of adjustment applied. Inclu-

sion and exclusion criteria should be clearly documented, and any exclusions applied after

data extraction should be justified using a clearly defined framework for evaluating data qual-

ity and outliers.

Annual online publication of WHO surveillance data points in

spreadsheet format

A spreadsheet table should be published annually on the WHO web site to allow for potential

inclusion of GRSN data by all groups in future estimates. At a minimum, rotavirus-positive

proportions

derived exclusively from acute watery U5 diarrhoea hospitalisations should be adjusted to

account for the proportion of total U5 diarrhoea hospitalisations that are acute watery. If the

rotavirus-positive proportion (r) is not reported for all clinical syndromes combined, then theequation r = ab + c(1 b) can be used, where a is the rotavirus-positive proportion amongacute watery U5 diarrhoea hospitalisations, b is the proportion of total U5 diarrhoea hospitali-sations that are acute watery, and c is the rotavirus-positive proportion among acute bloodyand persistent U5 diarrhoea hospitalisations combined. In the absence of local data to inform

parameter b, our analysis shows that acute watery diarrhoea is likely to be responsible for nomore than 87% (95% CI 8390%) of U5 diarrhoea hospitalisations. The true value of b is likelyto be lower because all data points included in the meta-analysis under-estimated the role of

persistent diarrhoea. Given that rotavirus is not associated clinically with acute bloody or per-

sistent diarrhoea, the value of parameter c is likely to be at least ~3% based on the rotavirus-positivity observed in healthy controls in GEMS.

Accounting for uncertainty in the steps used to convert rotavirus-positive

proportions into rotavirus-attributable fractions

The frequent asymptomatic carriage of many pathogens in the stools of healthy controls neces-

sitates the calculation of attributable fractions. To estimate the proportion of rotavirus-positive

cases that are attributable only to rotavirus, the population attributable fraction estimated by

the equation r AFe can be used, where r is the rotavirus-positive proportion reported amongU5 diarrhoea hospitalisations (all syndromes combined), and AFe is the rotavirus-attributablefraction among rotavirus-positive U5 diarrhoea hospitalisations (all syndromes combined).

Because it is rare for diarrhoea surveillance studies to include diarrhoea-free controls, very few

studies allow calculation of AFe. GEMS does include diarrhoea-free controls so permits thiscalculation; our new analysis of GEMS calculated the AFe to be 0.97 (95% CI 0.950.98). This

value was relatively consistent across all GEMS sites where it could be reported (Bangladesh,

India, Gambia, Kenya). This suggests that rotavirus is the attributable cause in almost all U5

rotavirus-positive diarrhoea hospitalisations. In a separate, related analysis, the rotavirus

attributable fraction was shown to increase by a factor of 1.08 (95% 1.021.14) when the more

sensitive qPCR test was used. This is similar (albeit slightly larger) than the adjustment made

to r to account for AFe, so both adjustments could reasonably be excluded, and this wouldhave a limited impact on central estimates of U5 rotavirus deaths. However, adjustments

applied to some pathogens and not others, would lead to inconsistent reporting of central esti-

mates (and uncertainty intervals) across enteric pathogens. These adjustments, and their

uncertainty, should therefore be reflected in future estimates for all enteric pathogens, includ-

ing rotavirus.

Further research into the clinical syndromes of U5 diarrhoea deaths, and

the real-world impact of rotavirus vaccines on those deaths

To date, all groups have assumed that the proportion of U5 diarrhoea hospitalisations caused

by rotavirus is a reasonable proxy for the proportion of U5 diarrhoea deaths caused by rotavi-

rus. This approach has been taken because hospitalisation is thought to be a good proxy for

diarrhoea that is sufficiently severe to lead to death. Two aspects of our analysis suggest this

assumption may lead to over-estimates of the number of U5 rotavirus deaths. First, we esti-

mate that acute watery diarrhoea is associated with 87% of diarrhoea hospitalisations but only

65% of U5 diarrhoea deaths. Higher case fatality ratios (CFR) have been reported for acute

bloody and persistent diarrhoea than acute watery diarrhoea [23] but more evidence on the

fatality of different syndromes is needed to corroborate this. In addition, the analysis of


diarrhoeal deaths relied on verbal autopsy reports which may be prone to recall bias, and our

analysis of diarrhoea hospitalisations only included those that became persistent after admis-

sion. Second, rotavirus was detected in a higher proportion of U5 acute watery diarrhoea hos-

pitalisations than U5 acute watery diarrhoea deaths in GEMS (44% vs 28%). Thus, among

children that had access to treatment, rotavirus was estimated to be less fatal than other causes

of acute watery diarrhoea. However, more evidence is needed on the effect of treatment on the

proportion of acute watery diarrhoea deaths due to rotavirus; in communities without access

to treatment services, rotavirus may represent a larger proportion of acute watery diarrhoea

deaths. Another explanation for the lower rotavirus-positivity among U5 acute watery diar-

rhoea deaths, is that the number of deaths captured in the 7 days after enrolment (n = 37) were

too few to make a reliable assessment. Longer follow-up periods allow more deaths to be

included but it then becomes increasingly difficult to ascertain whether children who were

rotavirus-positive at the time of enrolment were still rotavirus-positive at the time of death,

and whether cases that were negative at enrolment had a new rotavirus episode prior to death.

Further evidence is needed from other geographical locations on the distribution of clinical

syndromes among U5 diarrhoea hospitalisations and deaths. This should include a more accu-

rate assessment of the role of persistent diarrhoea among U5 diarrhoea hospitalisations. More

importantly, efforts should be made to accurately capture the real-world impact of rotavirus

vaccines on U5 diarrhoea deaths in early introducing countries. This will provide critical

insights into the true contribution of rotavirus to U5 diarrhoea deaths in different locations.

Presenting and incorporating the uncertainty in parameters used to

derive U5 rotavirus deaths

The uncertainty interval around the central estimates of U5 rotavirus deaths should be explic-

itly defined (e.g. the type of confidence or prediction interval) and should incorporate uncer-

tainty in each of the three core parameters (number of U5 deaths, % due to diarrhoea, % due

Fig 5. Global estimates of the number of rotavirus deaths

to rotavirus) as well as any other parameters used to adjust the original input data points e.g.

the parameters used to convert rotavirus-positive proportions into rotavirus-attributable

fractions.

Conclusion

There is considerable disagreement between global estimates of U5 rotavirus deaths, but it is

encouraging to note that estimates are converging over time, at least in absolute terms (Fig 5).

The aim of this analysis was not to recommend a single set of best estimates, but rather to

explain the reasons for differences, provide evidence to inform key areas of uncertainty, and

propose improvements for future estimates. Updates to GBD [24] and CHERG (now MCEE)

estimates were already well advanced during the course of this comparison study, and further

convergence is expected. The suggested improvements presented in this manuscript should be

incorporated, as far as possible, into future rotavirus mortality estimates. This is likely to be an

iterative and evolving process as new evidence emerges over time.

Supporting information

S1 Table. Information about the data used for new analyses.

(DOCX)

S1 Appendix. Further details on the comparison of rotavirus mortality estimates from

GBD, CHERG and WHO/CDC.

(DOCX)

S1 File. Country-level dataset used to compare CHERG, GBD and WHO/CDC estimates of

U5 deaths, U5 diarrhoea deaths and U5 rotavirus deaths in the year 2013.

(XLSM)

Acknowledgments

Disclaimer: The findings and conclusions of this report are those of the authors and do not

necessarily represent the official position of the Centers for Disease Control and Prevention

(CDC).

GRSN author group: Yati Soenarto (University of Gadjah Mada, Yogyakarta, Indonesia);

Celse Rugambwa (World Health Organization, Kigali, Rwanda); Evans Mpabalwani (Depart-

ment of Paediatrics & Child Health, Lusaka, Zambia); Jason Mwenda (World Health Organi-

zation, Brazzaville, Republic of Congo), Jill Murray, Adam Cohen (World Health

Organization, Geneva, Switzerland).

We acknowledge the many country-level collaborators involved in the GRSN, NRSN and

GEMS study sites. We acknowledge Ximena Riveros and Ana Maria Henao-Restrepo from

WHO Initiative for Vaccine Research, who helped to organise the initial meeting and bring

together the various rotavirus disease experts. We thank Ulla Griffiths and Mark Jit for provid-

ing useful comments on the paper.

Author Contributions

Formal analysis: Andrew Clark, Robert Black, Jacqueline Tate, Anna Roose, Karen Kotloff,

Diana Lam, William Blackwelder, Gagandeep Kang, James Platts-Mills, Colin Sanderson.

Investigation: Andrew Clark, Robert Black, Jacqueline Tate, Anna Roose, Karen Kotloff,

Diana Lam, William Blackwelder, Gagandeep Kang, James Platts-Mills, Colin Sanderson.


Methodology: Andrew Clark, Robert Black, Jacqueline Tate, Anna Roose, Karen Kotloff,

Diana Lam, William Blackwelder, Umesh Parashar, Claudio Lanata, Gagandeep Kang,

Christopher Troeger, James Platts-Mills, Ali Mokdad, Colin Sanderson, Laura Lamberti,

Myron Levine, Mathuram Santosham, Duncan Steele.

Writing original draft: Andrew Clark.

Writing review & editing: Andrew Clark, Robert Black, Jacqueline Tate, Anna Roose, Karen

Kotloff, Diana Lam, William Blackwelder, Umesh Parashar, Claudio Lanata, Gagandeep

Kang, Christopher Troeger, James Platts-Mills, Ali Mokdad, Colin Sanderson, Laura Lam-

berti, Myron Levine, Mathuram Santosham, Duncan Steele.

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death, 19902013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;

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2. Lanata CF, Fischer-Walker CL, Olascoaga AC, Torres CX, Aryee MJ, Black RE. Global causes of diar-

rheal disease mortality in children

17. Liu J, Platts-Mills JA, Juma J, Kabir F, Nkeze J, Okoi C, et al. Use of quantitative molecular diagnostic

methods to identify causes of diarrhoea in children: a reanalysis of the GEMS case-control study. Lan-

cet. 2016; 388(10051):1291301. https://doi.org/10.1016/S0140-6736(16)31529-X PMID: 27673470

18. IHME. Mortality estimation process. https://vizhub.healthdata.org/mortality/ [accessed 19th May 2016].

19. IGME. UN Inter-agency Group for Child Mortality Estimation. http://www.childmortality.org/ [accessed

18th March 2016].

20. Alkema L, You D. Child mortality estimation: a comparison of UN IGME and IHME estimates of levels

and trends in under-five mortality rates and deaths. PLoS Med. 2012; 9(8):e1001288. https://doi.org/10.

1371/journal.pmed.1001288 PMID: 22952434

21. Vos Theo B R, Phillips David E, Lopez Alan D, Murray Christopher J L. Authors Reply to Correspon-

denceCauses of child death: comparison of MCEE and GBD 2013 estimates. Liu Li, Black Robert E,

Cousens Simon, Mathers Colin, Lawn Joy E, Hogan Daniel R. Published Online May 23, 2015 http://dx.

doi.org/10.1016/S0140-6736(15)60663-8.

22. Stevens GA, Alkema L, Black RE, Boerma JT, Collins GS, Ezzati M, et al. Guidelines for Accurate and

Transparent Health Estimates Reporting: the GATHER statement. Lancet. 2016.

23. Bhandari N, Bhan MK, Sazawal S. Mortality associated with acute watery diarrhea, dysentery and per-

sistent diarrhea in rural North India. Acta Paediatr. 1992; 81 Suppl 381:36.

24. Mortality GBD Causes of Death C. Global, regional, and national life expectancy, all-cause mortality,

and cause-specific mortality for 249 causes of death, 19802015: a systematic analysis for the Global

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6736(16)31012-1 PMID: 27733281


52

5.0 Chapter 5 - Estimation of rotavirus age distributions in children aged

53

Global review of the age distribution of rotavirus disease in children aged

54

Abstract

Background: The impact of live oral rotavirus vaccines could be improved by adjusting the

schedules, but in published age distributions of rotavirus gastroenteritis (RVGE) the age bands

are too broad to allow a detailed investigation of the potential gains.

Methods: We sought datasets that could provide age distributions of rotavirus-positive

community cases, clinic visits, hospital admissions, emergency visits and deaths among

children

55

Introduction

Rotavirus gastroenteritis (RVGE) is estimated to cause around 200,000 child deaths each year

(1). Over half of the countries in the world now include live oral rotavirus vaccines in their

national immunization programmes (2). There are three vaccines licensed for global use

(Rotarix - GSK, RotaTeq - Merck & Co., and ROTAVAC - Bharat Biologicals), others

for national use (e.g. in Vietnam, China and India) and several others in the pipeline, including

neonatal and non-replicating injectable vaccines (3). Randomised controlled trials (RCTs)

have reported high vaccine efficacy (~90%) against severe RVGE in low mortality countries

but modest efficacy (~50%) in higher mortality settings (4). Alternative schedules are being

considered to increase their impact. A neonatal vaccine has had promising results in

Indonesia(5), and some studies have evaluated the potential of a booster dose given at around

9-12 months of age (6, 7). Several studies and surveillance systems have collected information

on RVGE age distributions but much of it is unpublished or has been published in age bands

that are too broad to allow a detailed assessment of the potential impact of alternative rotavirus

vaccination schedules. More granular age distributions would also help to quantify the number

of RVGE cases expected to occur at specific ages, so that changes can be monitored after

vaccination. More generally, there is a need to update the global evidence on RVGE age

distributions, compare them between countries and regions, and establish a reliable method

for extrapolating them to countries without data. An unpublished review was conducted in

2012 (8) but this did not include the large multi-country Global Rotavirus Surveillance

Network (GRSN) database (9), and several pivotal multi-country studies have also been

published since (10-12).

In this paper we aim to estimate granular age distributions of rotavirus disease outcomes in

children aged

56

Methods

Ethical Approval

This study was approved by the ethical committee of the London School of Hygiene and

Tropical Medicine (LSHTM); ethics reference 14398. All authors and countries gave their

consent to analyse and publish the data.

Search strategy and study selection

We sought country datasets containing counts of rotavirus-positive disease in children aged

57

distributions; and, papers without an accessible full text link. Two independent reviewers

(MHA, CL) screened abstracts and any ambiguity was resolved by a third reviewer (AC). A

letter was sent by email to the investigators of all studies identified in the systematic review.

Investigators were asked to provide anonymised data or complete a standard data extraction

table with counts by week of age up to 5.0 years. If the investigators did not respond before

the end of August 2017 and no other study was available for that country, we extracted the

age distribution reported in the publication. We included all country datasets that were

obtained from a previously unpublished literature and database search conducted by

Sanderson et al in 2012(8). This included articles published between 1990 and 2011.

All country datasets were combined into a central database with a standard format and list of

variables and analysed together with the GRSN datasets. We cross-checked datasets identified

through the literature search and GRSN to avoid data duplication. Prior to analysing the

datasets, we excluded studies that included fewer than 35 RVGE events, had known concerns

about EIA quality, had fewer than three age bands

58

reported by the UNPOP 2017 Revision(14). We grouped all datasets according to the under 5

mortality quintile of the country concerned, and calculated the median age and median best-

fitting parameters for each stratum. We also ran a series of regression analyses to explore

which combinations of variables would best predict the median age and parameters of the

chosen parametric distribution. To compare differences in rotavirus disease presentations we

plotted the full set of median ages reported for a given presentation against their respective

2010-2015 under-five mortality rates. We fit a least-squares line of best fit for each

presentation, reported the R-squared value and compared the best-fitting lines.

We used ArcGIS mapping software to display the median age of rotavirus hospitalisation

estimated for each country in the world. If more than a single dataset was available for a

country, we calculated the median age and median best-fitting parameters of all datasets for

that country. If no dataset was available, we assigned the median age of the countrys

corresponding mortality stratum.

Results

We identified 117 pre-vaccination datasets with rotavirus-positive events among children

59

example, in the very high child mortality stratum, the median age ranged from 29 weeks (IQR:

19-46) in Zambia to 50 weeks in Ethiopia (IQR: 30-81). Similarly, in the low/very low

mortality stratum, the median age ranged from 35 weeks (IQR: 19-64) in France to 101 weeks

(IQR: 65-157) in Ukraine.

Globally, most countries with a low median age were in Africa (Figure 3). In general, the

median age of rotavir

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